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Sample complexity of model-based search
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Source Annual Workshop on Computational Learning Theory archive
Proceedings of the eleventh annual conference on Computational learning theory table of contents
Madison, Wisconsin, United States
Pages: 259 - 267  
Year of Publication: 1998
ISBN:1-58113-057-0
Author
Christopher D. Rosin  The Scripps Research Institute and University of California, San Diego, CSE Dept., and The Scripps Research Institute, Mail Drop MB5, 10550 North Torrey Pines Road, La Jolla, CA
Sponsors
University of Wisconsin : University of Wisconsin
UC @ Santa Cruz : UC @ Santa Cruz
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGART: ACM Special Interest Group on Artificial Intelligence
Publisher
ACM  New York, NY, USA
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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
D. Aldous and U. Vazirani. "Go with the winners" algorithms. In S. Goldwasser, editor, Proceedings of the S5th Annual Symposium on Foundations of Computer Science. IEEE, 1994.
 
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S. Baluja and R. Caruana. Removing the genetics from the standard genetic algorithm. In A. Prieditis and S. Russell, editors, Proceedings of the Twelfth International Conference on Machine Learning. Morgan Kaufmann, 1995.
 
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D.A. Cohn, Z. Ghahramani, and M.I. Jordan. Active learning with statistical models. Journal of Artificial Intelligence Research, 4:129-145, 1996.
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S.A. Kauffman. The Origins of Order : Selforganization and Selection in Evolution. Oxford University Press, 1993.
 
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Jonas Mockus. Bayesian approach to global optimization : theory and applications. Kluwer Academic, 1989.
 
14
A.W. Moore and J. Schneider. Memory-based stochastic optimization. In D.S. Touretzky, M.C. Mozer, and M.E. Hasselmo, editors, Advances in Neural Information Processing Systems $, pages 1066-1072. MIT Press, 1996.
 
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P. Niyogi. Free to choose: investigating the sample complexity of active learning of real valued functions. In A. Prieditis and S. Russell, editors, Proceedings of the Twelfth International Conference on Machine Learning. Morgan Kaufmann, 1995.
 
17
J.G. Topliss. Quantitative structure-activity relationships of drugs. Academic Press, 1983.

Collaborative Colleagues:
Christopher D. Rosin: colleagues